NHESSNatural Hazards and Earth System SciencesNHESSNat. Hazards Earth Syst. Sci.1684-9981Copernicus PublicationsGöttingen, Germany10.5194/nhess-17-881-2017Brief Communication: A low-cost Arduino®-based wire
extensometer for earth flow monitoringGuerrieroLuigiluigi.guerriero@unisannio.ithttps://orcid.org/0000-0002-5837-5409GuerrieroGiovanniGrelleGerardoGuadagnoFrancesco M.RevellinoPaolaDepartment of Science and Technology, University of Sannio, 11
Port'Arsa street, 82100, Benevento, ItalyIndependent researcher, 5 Accesso alla Nazionale street, 83010,
Capriglia Irpina, Avellino, ItalyLuigi Guerriero (luigi.guerriero@unisannio.it)14June201717688188520February201722February20178May201716May2017This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/3.0/This article is available from https://nhess.copernicus.org/articles/17/881/2017/nhess-17-881-2017.htmlThe full text article is available as a PDF file from https://nhess.copernicus.org/articles/17/881/2017/nhess-17-881-2017.pdf
Continuous monitoring of earth flow displacement is essential for
the understanding of the dynamic of the process, its ongoing evolution and
designing mitigation measures. Despite its importance, it is not always
applied due to its expense and the need for integration with
additional sensors to monitor factors controlling movement. To overcome
these problems, we developed and tested a low-cost Arduino-based wire-rail
extensometer integrating a data logger, a power system and multiple digital
and analog inputs. The system is equipped with a high-precision position
transducer that in the test configuration offers a measuring range of 1023 mm
and an associated accuracy of ±1 mm, and integrates an operating
temperature sensor that should allow potential
thermal drift that typically affects this kind of systems to be identified and corrected. A field test,
conducted at the Pietrafitta earth flow where additional monitoring systems
had been installed, indicates a high reliability of the measurement and a
high monitoring stability without visible thermal drift.
Introduction
Earth flow activity alternates between long periods of slow and/or
localized movements and surging events (e.g. Guerriero et al., 2015). Slow
movement is normally concentrated along lateral-slip surfaces (Fleming and
Johnson, 1989; Gomberg et al., 1995; Coe et al., 2003; Guerriero et al.,
2016) which consist of fault-like segments (e.g. Segall and Pollard, 1980)
locally associated with cracks arranged in en echelon sets (Fleming and
Johnson, 1989). Movement velocity is controlled by hydrologic forcing, and
seasonal acceleration and deceleration are induced by variation of the
pore-water pressure (e.g. Iverson, 2005; Grelle et al., 2014). Thus, most
earth flows move faster during periods of high precipitation or snowmelt
than during drier periods, and the correlation between precipitation and
velocity is normally complex (Coe et al., 2003; Schulz et al., 2009). Earth
flow surges can occur when prolonged rainfalls are associated with the loss
of efficient drainage pathways (Handwerger et al., 2013) and new sediment
becomes available in the source zone through retrogression of the upper
boundary (e.g., Guerriero et al., 2014). In these conditions, the earth flow
material can fluidize and fail catastrophically.
Each different kinematic behavior materializes a specific hazard level that
needs to be quantified on the basis of monitoring data. An accurate
identification of hazard also includes the understanding of factors
controlling earth flow movement (Schulz et al., 2009). In this way, a
continuous record of earth flow displacement and its environmental drivers
is essential in defining the dynamic of the process (e.g. Corominas et al.,
2000). Additionally, for earth flow involving human infrastructures (e.g.
roads and railroads) displacement monitoring is crucial for understanding the
ongoing evolution and designing mitigation measures.
The Arduino-based extensometer after the assemblage. Major
electronic components are labeled.
Displacement monitoring can be completed with a variety of instrumentations
(e.g. rTPS, GPS), but most of them (i) do not allow
nearly continuous monitoring, (ii) imply time-consuming and expensive
monitoring campaigns and/or (iii) cannot be integrated with additional
sensors (Corominas et al., 2000). Wire extensometers are particularly
suitable for continuous monitoring, especially when it is concentrated along
well-defined shear surfaces, and can be easily integrated in multisensor
monitoring systems. Major disadvantages of extensometers are their cost (a
single-point high-performance sensor is sold at ∼ EUR 1000) and their sensitivity to temperature is also a function
of the characteristics of cabling systems. In this paper, we present a new
Arduino®-based wire-rail extensometer specifically developed
for monitoring earth flow movement. We chose the Arduino board because it
has been successfully used for the development of monitoring systems for
different applications (e.g. Bitella et al., 2014; Di Gennaro et al., 2014;
Lockridge et al., 2016). The system integrates a power unit, a data logger
and an operating temperature sensor, has a very low cost (∼ EUR 200), is configurable with different measurement ranges and
accuracy and has the potential to work with additional sensors. We test
extensometer performance at the Pietrafitta earth flow in southern Italy and
compare its measurements with those derived by successive GPS surveys and
discrete rTPS measurements.
Flow chart showing acquisition and storage logic.
Extensometer components, structure, and code logic
The extensometer is composed of (i) processing and storage modules, (ii) an
on-board operating temperature sensor, (iii) a linear position transducer, and
(iv) a power unit (Fig. 1; a simplified assemblage guide is reported in the
Supplement). The processing and storage modules are an Arduino Uno board
and a XD-05 data logging shield, respectively. The Arduino Uno board is a
user-friendly version of an integrated microcontroller circuit that uses an
ATmega238p low-power CMOS 8-bit microcontroller. It has 14 digital
input/output pins, 6 analog inputs, a 16 MHz quartz crystal, a USB
connection, a power jack, an ICSP header and a reset button (https://www.arduino.cc). The presence of multiple digital and analog
inputs make this platform ready for reading multiple sensors. The
data logging shield integrates a SD card read/write slot, a Real Time Clock
(RTC) module with coin cell battery backup and a prototyping area. In this
way, monitoring data are logged in a SD card at a predefined interval and
a date/time is associated. To choose this shield, we considered the presence
of the RTC module and its cost. We chose the cheapest. The operating
temperature sensor consists of a 10 K thermistor characterized by a tolerance
of ±5 %. It is installed with a reference resistor of 10 K in the
prototyping area of the logging shield (see wiring schematic in the code
attached as supporting material). For our test, the thermistor was
calibrated between -10 and 40 ∘C and obtained Steinhart–Hart
coefficients were used for temperature estimation. Steinhart–Hart
coefficients were calculated using a SRS Thermistor Calculator (http://www.thinksrs.com/downloads/programs/Therm Calc/NTCCalibrator/NTCcalculator.htm).
We estimated temperature error by comparing thermistor measurements with a
precision thermometer (accuracy ±0.05 ∘C) in laboratory
controlled conditions. The RMSE calculated on the basis of 40 observations
(between -5 and 35 ∘C) was ∼ 1 ∘C. The
linear position transducer is responsible for measuring cumulated
displacement and consists of a 1Kohms Bourns 3540S-1-102L precision
potentiometer equipped with a 3-D printed pulley. For our development and
test we used a pulley of 33 mm in diameter made of ABS (acrylonitrile butadiene styrene) plastic, the design
files of which (.obj and .skp) are reported in the Supplement. This allows a
measurement range of 1023 mm and an associated accuracy of ±1 mm
(nominal accuracy of 0.1 %). Such a range can be varied using a pulley
with different diameter. A change in range results in a change in accuracy
and resolution. The pulley was printed using a 3-D PRN LAB54 printer and an
ABS filament of 1.75 mm in diameter (specific density 1488 kg m-3). The
filament was extruded at 210 ∘C with a velocity of 30 mm s-1.
(a) The Pietrafitta earth flow in the Appenine mountains of
southern Italy, Campania region. The black star indicates the position of the
extensometer during the field test. (b) Installation configuration and monitoring
equipment for comparative analysis. (c) Installation scheme. (d) Results of
displacement monitoring with the extensometer and comparison with GPS
derived and rTPS results. Black circles indicate error associated with GPS
surveys. Operating temperature measured by the extensometer is also shown.
The system is powered using a 50 w solar panel and 12 V, 12 Ah battery. Since
the Arduino Uno has a broad power input range (recommended 7–12 V), and in
order to avoid overheating of the board connected to the use of a 12 V power
input voltage, a DC-DC converter is used to stabilize power voltage to 7.2 V.
The processing and storage module, the on-board operating temperature sensor
and the linear position transducer are housed in a 15 × 10 × 7 cm
waterproof box that, together with the power system, is housed in a second
larger 40 × 30 × 15 cm waterproof box. Such a modular structure is used to
protect both electronic and mechanic components from environmental conditions
and allow very short cables to be used that, as well as the modular structure,
prevent the system from thermal drift.
The code for the extensometer has been developed and compiled using the
Arduino IDE environment and open source code-string available online. The
logic of the code is reported in Fig. 2 and the code is reported in the
Supplement as well as the sensors wiring schematics. The final cost of the
extensometer was around EUR 200 including additional installation
equipment (see Table 1; e.g. rebars, wire, screw etc. …).
Additionally, even if it has been developed specifically for earth flows it
can be used for all types of landslide that move along well-defined
lateral-slip surfaces, and with specific improvements it can also be installed
in different position such as at the head of a landslide.
Individual cost and seller type of each component of the monitoring
system.
Components*Cost**Seller(EUR)Arduino Uno board22.0OnlineData logging shield10.0OnlinePrecision potentiometer18.0Online3-D pulley printing5.0Local10 k thermistor + 10 k resistor2.0LocalLed0.5LocalRTC coin cell battery2.5LocalDC-DC converter10.0Online50 W Solar panel + 12 Ah battery60.0Online+ 5 A regulatorInner box8.0LocalOuter box + cable glands36.0LocalCables + connector5.0LocalWood panel (40 × 50 cm)7.0LocalGlue + rivets10.0LocalRebars + screws25.0LocalExtensometer cable3.0Local(steel fishing line)Total224.0
* Minor components like board supports are not considered in the list because
they were already available.
** Online cost does not include shipping fees. Total shipping fees are around
EUR 35.
Installation and testing at the Pietrafitta earth flow
We test the extensometer performance at the Pietrafitta earth flow (Fig. 3a)
in the Apennine mountains of southern Italy (Campania region, Province of Benevento). Since 2006, this earth flow has been periodically
active,
exhibiting an alternation of slow persistent movements and rapid movement
especially localized at the toe of the flow. We chose this earth flow
because it is actively moving, its movement occurs largely along a lateral
well-defined shear surface (e.g. Gomberg et al., 1995) and is monitored
using both discrete GPS surveys and nearly continuous rTPS measurements. We
installed our low-cost Arduino-based extensometer along the left flank of
the earth flow toe (Fig. 3b). The installation was completed using a 2.5 m
long wire supported by several rebars, which forms a rail parallel to the
strike-slip fault, materializing the left flank of the flow. In this way, the
extensometer is dragged/moves along the flank registering the cumulative
displacement (scheme is shown in Fig. 3c) every 30 s. We used
available displacement data to make a comparative analysis of the monitored
displacement. To compare displacement measured with different systems, we
installed a GPS antenna screw mounting and a rTPS target on the wire
extensometer (Fig. 3b). Raw data measured with our monitoring systems are
shown in the graph of Fig. 3d. In particular, the earth flow toe moved
approximately 1 m in 6 days and 6 h. The average velocity calculated on
the basis of these data was ∼ 6.6 mm h-1. In this part of the
flow, the movement was largely dominated by the horizontal component. This
makes it possible to compare the displacement measured by the
extensometer and the horizontal component of the displacement vectors
reconstructed with both the GPS surveys and the rTPS. The comparison of the
results indicates that the total displacement measured by our extensometer
was approximately the same as that measured by combining GPS and rTPS surveys.
The difference between total displacement measured by the combination of GPS
surveys and rTPS and the extensometer was around 1.5 cm (1.5 %).
Additionally, the displacement time series reconstructed using rTPS data
perfectly fits the extensometer time series for the first 4 days of rTPS
monitoring, despite a slight thermal drift of the rTPS (see red curve of
Fig. 3d). In the successive 2 days the degree of fit seems to decrease and
affects the measured total displacement. This was probably also caused by
the deformation of the rail induced by the tilting of the ground surface
around the extensometer. Despite this drawback, the system exhibits a very
high monitoring stability without visible thermal drift, also at operating
temperatures higher than 35 ∘C.
Concluding remarks and possible future improvements
The Arduino-based extensometer was developed to provide a low-cost
improved platform for continuous earth flow/landslide monitoring. The
prototype was developed on the basis of the Arduino Uno board and integrated
a data logging RTC shield and an operating temperature sensor. It was
equipped with a high-precision position transducer that in the test
configuration offers a measuring range of 1023 mm and an associate accuracy
of ±1 mm. The field test indicates a high reliability of the measurement
and the importance of the rail setup. In particular, for horizontal
displacement monitoring it is important to consider the topography of the
surface of the flow and possible surface deformation caused by movement. In
this way, periodic inspection of the system needs to be planned. Major
advantages of the system are (i) the very low cost, (ii) the presence of an
integrated data logger, (iii) the potential to integrate it with additional
sensors, (iv) the possibility for use with different types of landslides.
Even though our test indicates the ability of the system to work in real
field conditions by providing reliable data, we have to consider that our test
was very short, and in only 6 days our extensometer reached the maximum
measurable displacement (average velocity of 6.6 mm h-1). Thus, for very low
velocities and very long monitoring periods it might be useful to use a 12 bit
Arduino DUE board that permits an increase of 4 times the resolution and/or the
range. The system can be integrated with a data transmission shield that
allows near real time data transmission and has the potential to be used in
landslide emergency scenarios. To further reduce the cost of the device it
would be possible to use the Arduino Pro Mini board that is cheaper than the
Arduino Uno and has a lower power consumption that allow to choose also a
cheaper power system and smaller housing boxes. Additionally, we have
planned to replace the ABS plastic pulley with an aluminium pulley that
should ensure a higher durability. This change might increase the cost of
the system.
Data are available upon request by contacting the corresponding
author (luigi.guerriero@unisannio.it).
The Supplement related to this article is available online at https://doi.org/10.5194/nhess-17-881-2017-supplement.
The authors declare that they have no conflict of interest.
Acknowledgements
We thank Rolf Hut and an anonymous reviewer for their constructive reviews
of the paper. We thank Remo Pedace of 3-D MAKERS (Avellino, Italy) for his
assistance in printing the pulley.
Edited by: T. Bogaard
Reviewed by: R. Hut and one anonymous referee
References
Bitella, G., Rossi, R., Bochicchio, R., Perniola, M., and Amato, M.: A Novel
Low-Cost Open-Hardware Platform for
Monitoring Soil Water Content and Multiple Soil-Air-Vegetation Parameter,
Sensors, 14, 19639–19659, 2014.
Coe, J. A., Ellis, W. L., Godt, J. W., Savage, W. Z., Savage, J. E., Michael,
J. A., Kibler, J. D., Powers, P. S., Lidke, D. J., and Debray, S.: Seasonal
movement of the Slumgullion landslide determined from Global Positioning
System survey and field instrumentation, July 1998 – March 2002,
Eng. Geol., 68, 67–101, 2003.
Corominas, J., Moya, J., Lloret, A., Gili, J. A., Angeli, M. G., Pasuto, A.,
and Silvano S.: Measurement of landslide displacements using a wire
extensometer, Eng. Geol., 55, 149–166, 2000.
Di Gennaro, S. F., Matese, A., Mancin, M., Primicerio, J., and Palliotti, A.:
An Open-Source and Low-Cost Monitoring System for Precision Enology,
Sensors, 14, 23388–23397, 2014.
Fleming, R. W. and Johnson, A. M.: Structures associated with strike-slip
faults that bound landslide elements, Eng. Geol., 27, 39–114, 1989.
Gomberg, J., Bodin, P., Savage, W. Z., and Jackson, M. E.: Landslide faults
and tectonic faults, analogs: the Slumgullion earth-flow, Colorado, Geology,
23, 41–44, 1995.
Grelle, G., Soriano, M., Revellino, P., Guerriero, L., Anderson, M. G.,
Diambra, A., Fiorillo, F., Esposito, L., and Guadagno F. M.: Space-time
prediction of rainfall-induced shallow landslides through a combined
probabilistic/deterministic approach optimized for initial water table
condition, B. Eng. Geol. Environ., 73, 877–890,
2014.Guerriero, L., Coe, J. A., Revellino, P., Grelle, G., Pinto, F., and
Guadagno, F. M.: Influence of slip-surface geometry on earth flow
deformation, Montaguto earth flow, southern Italy, Geomorphology, 219,
285–305, 2014.
Guerriero, L., Diodato, N., Fiorillo, F., Revellino, P., Grelle, G., and
Guadagno, F. M.: Reconstruction of long-term earth-flow activity using a
hydro-climatological model, Nat. Hazards, 77, 1–15, 2015.
Guerriero, L., Revellino, P., Luongo, A., Focareta, M., Grelle, G., and
Guadagno, F. M.: The Mount Pizzuto earth flow: deformational pattern and
recent thrusting evolution, Journal of Maps, 12, 1187–1194, 2016.
Handwerger, A. L., Roering, J. J., and Schmidt, D. A.: Controls on the seasonal
deformation of slow-moving landslides, Earth Planet. Sc. Lett.,
377–378, 239–247, 2013.
Iverson, R. M.: Regulation of landslide motion by dilatancy and pore pressure
feedback, J. Geophys. Res.-Earth, 110, 1–16, 2005.Lockridge, G., Dzwonkowski, B., Nelson, R., and Powers, S.: Development of a
Low-Cost Arduino-Based Sonde for Coastal Applications, Sensors, 16,
1–16, 10.3390/s16040528, 2016.
Schulz, W. H., Mackenna, J. P., Kibler, J. D., and Biavati, G: Relations
between hydrology and velocity of a continuously moving landslide –
evidence of pore pressure feedback regulating landslide motion?,
Landslides, 6, 181–190, 2009.
Segall, P. and Pollard, P. P.: Mechanics of discontinuous faults, J.
Geophys. Res.-Sol. Ea., 85, 4337–4350, 1980.